1. Field of the Invention
The invention pertains to systems for recovering original signal information or content by processing multiple measurements of a set of mixed signals, and more specifically, the invention pertains to adaptive systems for recovering original signals from among several received measurements of their mixtures.
2. Description of the Related Art
The recovery and separation of independent sources is a classic but difficult problem in signal processing. The problem is complicated by the fact that in many practical situations, many relevant characteristics of both the signal sources and the mixing media are unknown.
Two main categories of methods exist in prior art:
1. Conventional discrete signal processing (Please see U.S. Pat. Nos. 5,208,786 and 5,539,832), and 2. Neurally inspired adaptive algorithms (Please see U.S. Pat. Nos. 5,383,164 and 5,315,532).
Conventional signal processing approaches to signal separation originate in the discrete domain in the spirit of traditional digital signal processing methods that use statistical properties of signals. Such signal separation methods employ discrete signal transforms and filter/transform function inversion. Statistical properties of the signals in the form of a set of cumulants are used and these cumulants are mathematically forced to approach zero. This constitutes the crux of the family of algorithms that search for the parameters of transfer functions that recover and separate the signals from one another. Calculating all possible cumulants, on the other hand, would be impractical and too time consuming for real time implementation. Neurally inspired adaptive algorithms follow an algebraic method originally proposed by J. Herault and C. Jutten, now called the Herault-Jutten (or HJ) algorithm. The suitability of this set of methods for CMOS integration have been recognized. However, the HJ algorithm is at best heuristic with suggested adaptation laws that have been shown to work mainly in special circumstances. The theory and analysis of prior work pertaining to the HJ algorithm are still not sufficient to support or guarantee the success encountered in experimental simulations. Both Herault and Jutten recognize these analytical deficiencies and they describe additional problems to be solved. Their proposed algebraic algorithm assumes a linear static filtering with no delays. Specifically, the original signals are assumed to be transferred by the medium via a matrix of unknown but constant coefficients. To summarize, the Herault-Jutten method (i) is restricted to the full rank and linear static mixing environments, (ii) requires matrix inversion operations, and (iii) does not take into account the presence of signal delays. In many practical applications, however, delays do occur and and in many occasions the medium mixing exhibits nonlinear phenomena. Accordingly, previous work fails to successfully separate signals in many practical situations and real world applications.